In radio communication networks each base station usually holds a neighbor list of nearby transceivers, to which user equipments (UEs) might hand over the ongoing radio connection as they move. Such a list may for instance indicate the most suitable radio channels that need to be considered when performing a handover.
In many systems including universal mobile communication system (UMTS) and other systems based on code division multiple access (CDMA) scheme it is not practical for UEs to scan all possible channels or ID codes to find potential neighbors fast enough. Therefore, the neighbor list is downloaded from the serving transceiver, i.e. the serving base station, which gives information on where to listen out for neighbors, in terms of channels or CDMA code offsets, etc.
Neighbor lists are currently generated with a skilled manual process, looking at maps to visually identify adjoining sectors. Lists then have to be tuned to remove the neighbors that are never used and to add unlisted neighbors that may arise through anomalous propagation. Current tuning methods require skilled experts to identify neighbors on a map, followed by a costly and time consuming tuning process involving drive testing. Lists should be updated after any changes in the network such as adding new cell sites, or changes to RF parameter settings such as power or downtilt. Propagation and traffic conditions also change over time. Thus, the manual optimization is rather costly and time-consuming. Furthermore, drive tests can never be fully representative of where users really are, since most calls are made indoors.
The optimization process gets even more complicated if wireless networks with many different protocols are organized to work together. For instance, there may be a legacy 2G network, with smaller areas of 3G coverage plus a data overlay and occasional WiFi hotspots. It will be too complex a task to manually identify and maintain neighbor lists between all these types of access. Even though, after tuning, the final results are often acceptable, a significant effort is required. It is also necessary to keep lists up-to-date as changes occur in networks. Future wireless networks will be highly complex and interlinked, so manual methods may not be feasible. Therefore, better methods will be needed.